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Introduction: Machine Learning at the Atomic Scale.
Ceriotti M, Clementi C, Anatole von Lilienfeld O. Ceriotti M, et al. Among authors: clementi c. Chem Rev. 2021 Aug 25;121(16):9719-9721. doi: 10.1021/acs.chemrev.1c00598. Chem Rev. 2021. PMID: 34428897 No abstract available.
Machine learning meets chemical physics.
Ceriotti M, Clementi C, Anatole von Lilienfeld O. Ceriotti M, et al. Among authors: clementi c. J Chem Phys. 2021 Apr 28;154(16):160401. doi: 10.1063/5.0051418. J Chem Phys. 2021. PMID: 33940847
Unsupervised Learning Methods for Molecular Simulation Data.
Glielmo A, Husic BE, Rodriguez A, Clementi C, Noé F, Laio A. Glielmo A, et al. Among authors: clementi c. Chem Rev. 2021 Aug 25;121(16):9722-9758. doi: 10.1021/acs.chemrev.0c01195. Epub 2021 May 4. Chem Rev. 2021. PMID: 33945269 Free PMC article.
Machine Learning of Coarse-Grained Molecular Dynamics Force Fields.
Wang J, Olsson S, Wehmeyer C, Pérez A, Charron NE, de Fabritiis G, Noé F, Clementi C. Wang J, et al. Among authors: clementi c. ACS Cent Sci. 2019 May 22;5(5):755-767. doi: 10.1021/acscentsci.8b00913. Epub 2019 Apr 15. ACS Cent Sci. 2019. PMID: 31139712 Free PMC article.
Machine learning for protein folding and dynamics.
Noé F, De Fabritiis G, Clementi C. Noé F, et al. Among authors: clementi c. Curr Opin Struct Biol. 2020 Feb;60:77-84. doi: 10.1016/j.sbi.2019.12.005. Epub 2019 Dec 24. Curr Opin Struct Biol. 2020. PMID: 31881449 Review.
TorchMD: A Deep Learning Framework for Molecular Simulations.
Doerr S, Majewski M, Pérez A, Krämer A, Clementi C, Noe F, Giorgino T, De Fabritiis G. Doerr S, et al. Among authors: clementi c. J Chem Theory Comput. 2021 Apr 13;17(4):2355-2363. doi: 10.1021/acs.jctc.0c01343. Epub 2021 Mar 17. J Chem Theory Comput. 2021. PMID: 33729795 Free PMC article.
159 results